The present disclosure relates in general to image detection and/or recognition. More specifically, the present disclosure relates to systems and methodologies for reliably and continuously detecting objects in a continuous surveillance video system across significantly varying conditions, such as weather conditions and time of day.
Intelligent Video Analytics (IVA) describes a class of surveillance video systems that focuses on automating video analysis and security alerts, thus reducing the need for most manual monitoring and its associated inefficiencies and costs. A typical IVA system includes digital video technology integrated with analytical software. The video analytics software may run on a networked device, such as a sophisticated IP (internet protocol) camera, in an embedded system or on a computer-based computing device. In a networked configuration, the IP camera records video footage and the resulting content is distributed over an IP network.
Visual object detection is a key component of IVA systems. In the past decade, significant progress has been made in the area of visual object detection. However, many challenges remain to be addressed in order to develop reliable detectors (i.e., classifiers) that run continuously over extended periods of time and under varying operating conditions. For example, certain environments, such as urban settings, present unique challenges due to significant object appearance variations caused by lighting effects such as shadows and specular reflections, object pose variation, multiple weather conditions, and different times of the day (e.g., day and night).